DUAL PHYSICALLY-DRIVEN AND DATA-DRIVEN METHOD FOR RECONSTRUCTING INTERNAL RESPONSE OF BRIDGE

    公开(公告)号:US20240289508A1

    公开(公告)日:2024-08-29

    申请号:US18410994

    申请日:2024-01-11

    CPC classification number: G06F30/13 G06F17/16

    Abstract: Disclosed is a dual physically-driven and data-driven method for reconstructing internal response of a bridge. The method includes: obtaining acceleration response by an acceleration sensor under an action of an unknown load of the bridge; embedding a physical logic into a neural network based on a frequency response function; putting a physical formula and corresponding boundary conditions and initial conditions into a loss function as penalty terms, and limiting a space of a feasible solution accordingly; and training a neural network model, and predicting acceleration of an unknown point by inputting an acceleration response set of a known point obtained by the sensor into the network. The formula is solved by converting direct solving of a control formula into optimization of the loss function, such that the problems that the internal response of the bridge is difficult to measure and excessively depends measured data can be effectively solved, and accuracy and robustness of internal response prediction of the bridge can be improved.

    BLOCKCHAIN-BASED ELECTRICITY TRADING METHOD AND SYSTEM IN VIRTUAL POWER PLANT ENVIRONMENT

    公开(公告)号:US20240170963A1

    公开(公告)日:2024-05-23

    申请号:US18307937

    申请日:2023-04-27

    CPC classification number: H02J3/008 G06Q40/04 G06Q50/06 H02J3/003

    Abstract: A blockchain-based electricity trading method and system are disclosed. Based on the initial trading plan of the user in the virtual power plant, a non-cooperative game model among multiple users and the virtual power plant is constructed, a purchase price, a sale price and a demand response compensation price of a trading between the user and the virtual power plant during t period are determined; according to the above results, a final load demand of user i, a charging capacity or discharging capacity of the energy storage device of user i, as well as a purchase electricity quantity or sale electricity quantity of a trading with the virtual power plant during t period are determined, and a final trading scheme is formed; and based on the final trading scheme, both trading parties are matched, a trading contract is generated and a verification is performed.

    MEASUREMENT SYSTEM FOR DETECTING DEEP-HOLE SURFACE TOPOGRAPHY BASED ON LOW-COHERENCE INTERFEROMETRY

    公开(公告)号:US20240167812A1

    公开(公告)日:2024-05-23

    申请号:US18469792

    申请日:2023-09-19

    CPC classification number: G01B11/2441 G01B9/0209

    Abstract: A measurement system for detecting deep-hole surface topography based on low-coherence interferometry (LCI), can include a detection part and an autocollimation system. The detection part includes a white light interferometric system, which specifically includes a 1550 nm amplified spontaneous emission (ASE) broadband light source, a first reflector, a first beam splitting prism, a second reflector, and a reference reflector that are arranged in sequence, where a to-be-measured deep-hole and a near-infrared camera are respectively arranged at two sides of the first beam splitting prism, and a conical prism is disposed inside the to-be-measured deep-hole. The autocollimation system is disposed between the to-be-measured deep-hole and the first beam-splitting prism. The autocollimation system includes a 630 nm light source, a dichroic prism, a second beam-splitting prism, a third reflector, and a quadrant detector that are arranged in sequence.

    MULTI-ENERGY INTEGRATED SHORT-TERM LOAD FORECASTING METHOD AND SYSTEM

    公开(公告)号:US20240146057A1

    公开(公告)日:2024-05-02

    申请号:US18307926

    申请日:2023-04-27

    Inventor: Kaile ZHOU Rong HU

    CPC classification number: H02J3/003 H02J2203/20

    Abstract: The disclosure provides a multi-energy integrated short-term load forecasting method and system, which relates to the technical field of load forecasting. In the disclosure, after classifying the acquired relevant data of multi-energy integrated short-term load forecasting, the data after sample classification is used to train the multi-energy integrated short-term load forecasting model. The model is composed of multiple layers of temporal convolutional networks having multi-head self-attention mechanism and rotary position embedding. Finally, the trained model is used to carry out the multi-energy integrated short-term load forecasting. The disclosure can fully mine the coupling feature between multi-energy loads, improve the accuracy of multi-energy integrated short-term load forecasting, and further improve the management level and service efficiency of integrated energy demand side.

    METHOD OF PREPARING INDOLIN-2-ONE COMPOUND AND METHOD OF USING INDOLIN-2-ONE

    公开(公告)号:US20240043383A1

    公开(公告)日:2024-02-08

    申请号:US18178765

    申请日:2023-03-06

    Inventor: Mei LUO

    Abstract: A compound, having a structure represented by a formula (I),




    and prepared by one pot synthesis of benzophenone hydrazone, 7-chloroisatin, and copper(II) acetate monohydrate, and refluxing in 100 mL of anhydrous methanol solvent for 48 hrs. A method for preparing the compound includes: collecting and placing 0.0235 g of benzophenone hydrazone, 0.6914 g of 7-chloroisatin, and 0.6720 g of copper(II) acetate monohydrate complex in a 100.0 mL flask; adding 50 mL of anhydrous methanol as a solvent; stirring a resulting mixture at room temperature for 48 hrs; performing column chromatography separation, and elution with petroleum ether/dichloromethane in a volume ratio of 1:1, and collecting final component points and naturally volatilizing the final component points to obtain 7(E)-chloro-3-diphenylmethylindolin-2-one crystals. The compound is used as a catalyst for reaction between benzophenone imine and trimethylsilonitrile, and has a catalytic effect with a conversion rate reaching 99%.

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